Discussion and comment on the latest research in business, economic and financial history

About Fernando Arteaga

I am PhD Economics Student in George Mason University. My research interests lie in the fields of Economic History, New Institutional Economics and Agent-Based Modeling. I am also interested in banking and monetary economics; my undergraduate dissertation centered on the evolution of the debates over the "management of money" (free banking and other schemes). My graduate dissertation (which I'm working on right now) dwells on the institutional properties that create incentives for political union and fragmentation (why some nations are large and some small); I focus on the case of the Spanish Empire in the 16th-19th century (and the process of fragmentation that led to the creation of the Latin American countries)

Abstract: Does the economic effect of immigrant women differ from that of immigrants in general? This paper examines if gender has influenced the short- and long-term economic impact of mass migration to the US, using Census microdata from 1880 and 1910. By means of ordinary least squares and instrumental variable estimations, the analysis shows that a greater concentration of immigrant women is significantly associated with lower levels of economic development in US counties. However, immigrant women also shaped economic development positively, albeit indirectly via their children. Communities with more children born to foreign mothers and that successfully managed to integrate female immigrants experienced greater economic growth than those dominated by children of foreign-born fathers or American-born parents.

What is the economic impact of female migration? The authors seek to answer the inquiry by using the United States in the late 19th and early 20th century as their study case. The goal of the paper is to highlight the distinctiveness of women immigration (compared to that of men), both in the processes that led women to migrate, the characteristics they had, and the places where they finally settled. The main thesis of paper stresses the long-lasting effect women have had; through their family role, as mothers, they facilitated the formation and transmission of social capital, which had a pervasive positive effect on income.

Female migrants in early America tended to settle mainly on urbanized areas in the Northeastern coast – compared to that of male immigrants (who settled mainly in the South and West). The migration levels of women, in absolute terms, were lower, and their marriage rates higher. More importantly, their labor participation rates were low: women tended to stay and work in domestic chores rather than find occupations in the market. These characteristics make female migration distinct to that of men, and motivate the goal of the paper in trying to assess their particular relevance.

Figure 1: Immigrant Women in the United States, 1880. By the nature of the variable, counties with a larger share of immigrant women imply a lower share of immigrant men.

The text relies on standard econometric analyses, based on intuition and on the literature of migration and culture transmission. The main data sources are the historical censuses of 1880 and 1910, which capture the amount of, male and female foreign-born population residents in each US county (among other data). The paper presents two base regressions that aim to assess the direct and indirect economic impact of female migration, both in the short and the long term. The first model regresses economic income (GDP per capita by county) on female migration (foreign-born women as a share of the total population in the county). They find that the variables are negatively correlated: lack of labor market participation hindered the female contribution to income. The authors also found that this has had a long term negative effect (income today is also negatively correlated with female migration in late 19th and early 20th century) [1]. To correct for potential biases and to establish a causality linkage that goes strictly from migration to income, and not the other way around, the authors use three different instruments: a) the percentage of married persons; b) the number of persons living in a household; c) the urbanization rate of the county being examined. The first instrument accounts for the fact that female migrants tended to be married in larger shares than the rest of the population. The second accounts for the idea that migrants, especially women, tended to stay with members of their families through their lifetime. The last one maintains that female migrants favored settlement in urbanized zones. The validity of an instrument (marriage percentage, household size and urbanization) hinges upon it being correlated with the dependent variable (income) only by it causing the highlighted mechanism (female migration). The authors do several post-hoc statistical tests to evaluate the instrument’s validity and conclude that it is indeed a valid and strong one. In any case, the instrument variable outcomes do not change the results of the baseline ordinary least squares scenario, they just allow a more robust interpretation of them: it can be said that female migration did have a negative impact on income.

The second model emphasizes the indirect impact of migrant women. Maybe women themselves did not positively contribute to the economic wellbeing of their communities, but they could have done so through other means. The authors refer to the literature that stresses how mothers influence their children behavior and thus have an important role as social capital transmitters (which could positively affect economic wellbeing). They regress economic income today on the share of children (in 1880 and 1910) born from: 1) a migrant mother and an American-born father; 2) a migrant father and an American mother; 3) both American parents. The standard base of comparison is the share of children that had both parents as immigrants [2]. By definition, the model can only capture the long-term effect of female migrants. The authors find that US counties with an historical larger share of children with migrant mothers are correlated with larger incomes today – in comparison to the other explanatory variables; having American parents is negatively correlated with income today; having a migrant father, and American mother, has a non-significant and null effect on economic outcomes today. The argument, again, rests on the case of social capital transmission: women, as mothers, matter very much. To corroborate their OLS results they also use an instrumental variable. The authors assume that American-born women that had migrant mothers followed the cultural transmission pattern established by their forebears. They call this the “supply-push” component, which they estimate and use as their instrument. Just as the first model, the instrumental variable inclusion does not modify the basic results, it only permits to talk about causality from migrants in the past to better economic outcomes today.

In conclusion, the paper finds that female immigration, while having a negative direct short-term impact on economic income, has a long-lasting positive effect through the “cultural carrier” channel.

Comment

The paper is a very interesting one, being one of the few studies that aims to disentangle the impact of women as migrants compared to that of men. The results the authors present make intuitive sense. I would like to make just small technical comments based on the variables they use and how they use them.

First, related to the semantics of the concept of “migration.” Migration is normally thought as a flow variable, but here it is used as a stock variable. Given the data they use (measuring migrants as people classified as foreign born in two censuses) the authors cannot measure the impact of migration as a flow, only the impact of it in broad terms. This is not a problem. I just would have liked to see a minor explanation on the paper that clarified the interpretations that we could get out of this. In fact, I think it could explain why they find a negative impact of migrant women in income (if the variables were flows, through migration rates and economic growth, the results may be different).

Second, on a more technical note, I’m skeptic of the instruments being used. Even though the authors argue that they are valid and strong, I remain unconvinced. The authors show that all four of them are correlated with the dependent variable and uncorrelated with the error terms, yet there is almost no explanation, backed up by a narrative, of how exactly these instruments impact on income only through female migration. For each one of the instruments used I could think of other alternate channels by which they could impact income. For example, the use of percentage of marriage by county could indeed be correlated with female migration, but is that the only potential channel? Could it not be that maybe poverty or religion could be impacting income as well?

Lastly, I wish the narrative part could be explained in larger detail. For example, how exactly female migrants in 1880 have a direct impact on income in 2010. Or how exactly children of foreign mothers in 1880 and 1910 could affect income today. It is one thing to say that culture matters, it is another different thing to point how exactly it does. In fact, even though they do mention the pervasiveness of cultural traits through time, they fail to mention that this pervasiveness does not imply ipso facto a good outcome is assured. Sometimes, social capital is also correlated with bad outcomes.

[1] The authors do not provide a concise explanation of why this could be happening: how could a century year old female migration pattern directly impact economic wellbeing today?

[2] All the interpretations of results are in comparison to that baseline.

Abstract: We find that lower rainfall in north-central Europe (Gaul/Germania) predicts more assassinations of Roman emperors from 27 BC to 476 AD. Due to agricultural pressures on Germanic tribes, low precipitation caused more barbarian raids. These raids, in turn, weakened the Empire’s overall political stability, and reduced the costs of assassinating an emperor. We buttress our empirical analysis with case study evidence.

Was Imperial Rome’s political stability disturbed by environmental shocks? If so, what were the transmission channels? These are the two fundamental questions the authors aim to answer. Their thesis is straightforward: As any pre-industrial society, rainfall levels predicted agricultural output in Roman times. A lack of rain affected food availability, especially in the underdeveloped regions where Northern Germanic Tribes resided, making these societies more prone to raid Roman towns across the border. The incursions then created political conflict among the Romans themselves.

The text relies on econometric analyses and a couple of case studies to back up the argument. The main statistical test is simple: they regress Roman political stability on rainfall data. The main variable they use as a proxy of political unrest is the assassination of Roman emperors (as presented by Scarre 1995): the more emperors were killed, the less stability in the Empire. Alternatively, they also employ an index of inflation and new governmental infrastructure investment as a proxy for stability (larger inflation and less imperial projects imply improved stability). The rainfall variable comes from Buengten et al. (2011) own estimations on precipitation levels across France and Germany for all the period under study. Figure 1 displays the main data points used in the analysis. The authors find that negative rainfall shocks are both associated with more emperor’s being killed (Figure 2) and with having larger inflation rates and fewer investment projects. A decrease of one standard deviation in precipitation caused an 11.6% standard deviation increase in assassination probability. The regression is empirically valid because there is no possibility of reversal causality; precipitation is not a factor that may be influenced by Roman politics [1].

Figure 2: The red line indicates the precipitation level, while the blue is the amount of Roman Emperors assassinated.

But how exactly does lack of rain destabilized Roman society? The paper’s hypothesis relies on the Germanic raid linkage: Germanic tribes attacked Rome when they had a poor harvest of their own, which then created unrest in Roman interior stability. To test such assertion, they regress Germanic/Gaul incursions on the rainfall levels. The raid data they use comes from Venning (2010), who reviewed the many times the Roman Empire suffered raids through its history. The authors find a negative correlation: a decrease in one standard deviation in rainfall is associated with a 4% standard deviation increase in a number of raids. They corroborate the results by doing some robustness tests: 1) a placebo test, in which they regress non-Germanic raids on precipitation levels, which they find that had insignificant impact (which means that precipitation mattered only in Germanic zones, because they were the only ones that really suffered from a lack of rain); 2) an instrumental variable where the relationship between Roman instability and Germanic incursion is instrumented by rainfall. They find that “a standard deviation increase in the raid dummy [the presence of raiding] causes a 29.3% increase in the probability of assassination.”

To give more weight to their results, they present a brief recapitulation on the reigns of two assassinated Roman emperors: Severus Alexander (208-235) and Gallienus (218-268). The key insight is that both emperors faced important challenges on the Eastern and Northern borders, however only the latter had a relevant impact on Roman internal politics. On the East, the Roman Empire frequently collided with the Sassanid Empire (the other larger state in the area), but notwithstanding the severity of the clashes (at some point they even captured a Roman Emperor, the father of Gallienus) it never caused great civil unrest in Rome. However, on the North, Rome bordered the Germanic tribes (scattered non-organized societies) that did affect Rome’s stability. The conclusion we get from the narrative is that the Germanic border was important/special precisely because it was very susceptible to environmental shocks, which then led to constant raiding; unlike the Sassanid border, in which the Romans faced a cohesive society that could successfully resist bad crops or confront military bravados on non-environmental factors.

Comment

I enjoyed reading the paper very much. It made me re-realize why I find Economic History fascinating: it deals with topics that are interesting in themselves (the politics of the Roman Empire! What is not to like about it?), that remain relevant for today’s problems (we still seek to understand the relationship between nature and political conflict very much), and it treats the issues under study with great care and humility (there is no grand universal theory, but a careful attempt to attain a reliable empirical finding- however small that is).

My main concern with the paper is that the authors never clarify the relationship between Northern Rome’s lack of state capacity and the barbarian incursions. The main narrative maintains that the Germanic raids were the source of Roman political unrest (that is the way I summarized the argument in the preceding section). But at several instances across the paper, the authors hint that Roman political complications in Gaul were themselves a precursory factor that made the Germanic incursions more menacing.

The problem is present in both the econometric analysis and in the case studies. If I understood it correctly (by looking at figure 1), the regressions they asses rely on data that captures rainfall in both Roman Gaul/Germania and non-Roman Germania. The argument is that lack of rain affected Germanic independent tribes more because they were less prepared than the Roman borderline towns. Intuitively, this sounds right. However, the assertion does not imply that alternative transmission channels could not matter too. Yes, Roman towns were better prepared to endure bad harvests than their Germanic neighbors, but that doesn’t imply that bad agricultural output in Roman towns could not be the cause of political instability in them. There may be a relevant omitted variable bias problem in the empirical specification. [2]

The problem seems clearer when we consider the conclusions the authors get from their case studies: in them, they compare the level of relevance local border town problems in Germania/Gaul and in Syria had on larger Roman politics. The Germanics were a constant thorn on Rome, but the Syrians weren’t. Why? The authors explicitly stress that Roman Gaul/Germania had lower state capacity than Roman territories next to Syria, and so it was easier to subdue unrest in Syria than in Gaul. However, if that is so, then we are led to beg the question of what causes what? Is weak state capacity due to raiding, or is raiding due to weak state capacity? The paper’s narrative emphasizes the former linkage (all of the quantitative estimations rely on that sole mechanism too) while, at the same time, it recognizes that the latter mattered too. Unfortunately, it never sets to disentangle the underlying causality. [3]

Venning, Timothy. (2010) A Chronology of the Roman Empire, Bloomsbury Academic: New York.

Endnotes

[1] The authors confirm this by regressing rainfall at time t on lagged t -1 political stability. It is interesting to note that this obvious observation may not be true for current events. Climate change is indeed affected by the domestic politics of some countries.

[2] I also remain confused about what data was used for some of the alternative estimations. For example, on the placebo test, they regress non-Germanic raids on precipitation levels. I assume they are using non-Germanic precipitation levels too. Otherwise, it would mean they would be testing how rain in Germania affects raids in non-Germania, which would make no sense. However, they don’t clarify.

[3] My two cents on the Syrian/Gaul distinction is that geography and travel times may explain it. ORBIS (A project that reenacts the geospatial framework of the Roman Empire) allows us to estimate the times and cost of regular trips to different cities in the Roman Empire. A trip from Rome to Cologne would last 32 days on the fastest route and 63 days on the cheapest. A trip from Rome to Palmyra, on the other hand, would last 28 on the fastest route and 42 on the cheapest. This can provide a benchmark of the cost of mobilizing resources across regions: moving a Roman army could be 1/3 cheaper if it had to go to Syria rather than Germania. This significative figure implies that the costs of subduing unrest in Germania were larger and so more difficult.

The Historical State, Local Collective Action, and Economic Development in Vietnam

Abstract – This study examines how the historical state conditions long-run development, using Vietnam as a laboratory. Northern Vietnam (Dai Viet) was ruled by a strong centralized state in which the village was the fundamental administrative unit. Southern Vietnam was a peripheral tributary of the Khmer (Cambodian) Empire, which followed a patron-client model with weaker, more personalized power relations and no village intermediation. Using a regression discontinuity design across the Dai Viet-Khmer boundary, the study shows that areas historically under a strong state have higher living standards today and better economic outcomes over the past 150 years. Rich historical data document that in villages with a strong historical state, citizens have been better able to organize for public goods and redistribution through civil society and local government. This suggests that the strong historical state crowded in village-level collective action and that these norms persisted long after the original state disappeared.

What was the impact of the ancient Vietnamese Dai Viet empire in promoting long-term economic development? That is the main question the authors try to assess. Their inquiry is embedded within the now large literature on the importance of culture and institutions, as deep determinants of growth. The contribution the paper makes is, however, not restricted to adding one more piece of evidence in favor of it, but, more importantly, in providing empirical support for a specific transmission channel: how state capacity can be built through time via the fostering of local self-organization capabilities.

The paper’s main story builds on the idea that two distinct meta-societies existed within East Asia, and idea around which, by the way, there is general agreement. One of these societies based on Chinese precepts, prevalent in the Northeastern region; and other spread in the Southeast throughout the Indian Ocean. Societies of the former category were historically constituted around a sort of Weberian professional bureaucracy that consolidated the working of a central state. The latter depended more on informal networking mechanisms among local elites to survive, and hence, tended to promote hierarchical patriarchal relationships.

Today’s Socialist Republic of Vietnam (henceforth Vietnam) is an interesting case study precisely because it arose out of the union of those two distinct cultures. The northern part, the Dai Viet, is an example of a Sino-style state, while the southern part of Vietnam (initially part of the Champa State and later as part of the larger Khmer Empire) resulted from a Indo-style society. Figure 1 below offers map of present day Vietnam aligned with the size of the historical Dai Viet empire. Figure 1 suggests the Dai Viet expanded southwards through time but ended up establishing its final frontier in 1698 (orange color). It is this border the authors think provides a natural experiment that allows a clean regression discontinuity (RD) strategy that permits the disentanglement of the effect of being part of a bureaucratized state vis a vis a patriarchal state.

Figure 1: Dai Viet Historical Boundaries (Dell et al., 2017)

The use of the RD design is appropriate, the authors argue, because the chosen border resulted from exogenous contingencies that do not reflect any difference in future economic potential. The 1698 demarcation was settled on the ridges of a river, but there was nothing else particular to it that made that boundary preferable to other potential borders. The Dai Viet stopped its expansion because of constrains imposed by a local civil war (something that has nothing to do with the river itself). Moreover, the environmental characteristics of both sides of the river are almost identical (or vary smoothly), so there is no important geographical difference either. The only thing that changes abruptly is that on the east shore of the 1698 border, Dai Viet settlers occupied and controlled the land, while Khmer villagers occupied and controlled the land to the west of the river. Another possible counterargument to the use of the 1698 border as a natural experiment is the relevance of migration: if settlers moved across villages (at any time after the establishment of the original border), then the boundary becomes inconsequential. The authors argue that, even though they do not have historical data to control for it, there is qualitative evidence that refers to negative attitudes towards outsiders within the villages, which constitutes an important constraint to any major migratory flow. Today, both sides are part of Vietnam. It is then possible to assess if Die Viet institutions still exert some type of effect in current economic outcomes.

Figure 2 portraits the main outcome of the paper. Using household expenditure data from recent censuses (2002-2012), the authors find that today, villages situated along the historical Die Viet side of the border earn a third more than those communities that are situated on the historical Khmer side (Within the figure, the darker the zone depict lower earnings).

Figure 2a: Household Consumption, RD Graph (Dell et al., 2017)

The authors, however, not content with establishing the effects on current outcomes, look for historical evidence too. They collect data from different periods of Vietnamese history: 1878-1921 for the French Colonization, 1969-1973 for the South Vietnam State, and 1975-1985 for the early Communist Period; and find that the pattern is persistent through time: The Diet Viet zone is, in general, more developed than the Khmer side.

How can these results be interpreted? The income differences must be due to the Die Viet heritage of greater state capacity that acted through local community self-organization that made them more co-operative and facilitated the resolution of local collective action problems. To test whether this transmission channel matters, the authors looked for data on social capital. Their main sources were the surveys and census of the South Vietnamese period. What they find corroborates their story: villagers on the Diet Viet side were more prone to participate in community activities, to collect more taxes (that at the time were local responsibility, not provincial), to have greater access to public goods (health, school and law enforcement), to be skeptical of central government in favor of local, and to give more to charity.

Comment

All in all, the authors do a thorough job in assessing the robustness of their main story. They control for several of potential alternative stories and/or possible variables that could affect the results and mechanisms. Any critique of it may sound redundant or unreachable. Yet, I would point to three different aspects that may be important.

First, and perhaps most importantly, I would stress that although the argument makes sense, the narrative is unclear as to how specifically the Dai Viet, which supposedly was a centralized bureaucratized state, fostered local governance. As the authors mention in the introduction, the literature on social capital is ambivalent on its effects on economic outcomes. As it is, the paper’s contribution is the finding of empirical evidence on the presence of a particular transmission channel (from state to local governance), but without a clear model and/or an analytical narrative, we are left in the dark about how explicitly this mechanism worked its way throughout society.

Second, and pushing the level of pickiness even further, one can always speak of a potential omitted variable bias. I must ask then: what about genes? The authors minimize ethnic fragmentation as a problem because they find the studied area is cataloged as being almost entirely composed of homogeneously ethnic Vietnamese. The problem is that censuses and surveys may under-report true ethnicity, and cannot capture genetic differences at all. By the authors’ own account, we are told the Diet Viet State originated as, and remained for a long time, Chinese. Moreover, as Tran (1993) attests, Chinese ethnicity may conflate the results of the paper in other several ways:

the largest Chinese migration occurred between the late 17th century and early 19th century, just at the time that the Dai Viet-Khmer border was being established;

The Chinese settled mostly in southern Vietnam, the part that the authors use as study case;

Chinese early importance resided precisely in that they helped establish new villages and trade outposts. They (not merely the Diet Viet heritage) helped to build local governance structures.

If ethnicity has been underreported and/or Chinese genetics matter in fostering economic development in any way (as suggested by Ashraf-Galor, 20013a, 2013b) then the interpretation of the paper could dramatically change: the importance of the Dai Viet state would be downplayed in favor of just being more ethnic/genetic Chinese. After all, it is known that there is a correlation between having larger ethnic Chinese minority and larger economic growth (Priebe and Rudulf, 2015).

Third, related to the last point: one would expect that given the importance of the result – the long-term reach of Diet Viet institutions–, its impact would feel more broadly across all the territory, not only in the immediate zones of the frontier which were the last to be incorporated into the state. Figure 3, for example, shows the level of poverty in Vietnam (Epprecht-Heinmann,2004). It is visible that the area under study (along the last border of the historical Diet Viet) has the lowest share of poverty in the whole country. The immediate area to the left (which coincides with the area that historically belonged to the Khmer Empire) is poorer indeed. But the differences are minor if we compare them to the rest of current Vietnam, which belonged almost entirely to the Diet Viet, and has the largest poorer areas. The RD design may be identifying a non-observable variable that is concentrated in the southern part (like ethnicity or/and genes) and is not broadly distributed across the rest of Vietnam.